Understanding
the functional connections between different regions of the brain presents a
major challenge in neuroscience. A number of statistical techniques have been
developed to determine functional connectivity among populations of neurons.
However validation of these techniques has typically relied on either
macroscopic anatomical information or computer simulations for want of a living
system where connectivity is known or constrained a priori. Fabrication of
special devices [1] in our lab has enabled us develop
dissociated cultures of neurons which are predominantly unidirectional, and
when coupled with 60 electrode microelectrode arrays (MEA), the extracellular
recordings from this in vitro system (Fig 1) provide a valuable platform to
validate these statistical measures. These devices, fabricated from PDMS, are
composed of two microwells, each containing approximately 20,000 neurons,
connected by 51 microtunnels with dimensions: 3 x 10 x 400 µm (h x w x l). The
devices were then placed over an 8x8 grid of electrodes (Multichannel Systems,
electrode spacing 200 um) in which electrodes could simultaneously measure
spike propagation along the tunnels and activity within and between each well.
To create unidirectionally connected cortical populations, one well (input) was
plated with E-18 cortical neurons and after axons had extended into the tunnels
at 10 days in vitro, the second well (output) was plated. In essence, this
creates a simple feedforward network in which the number of connections can be
manipulated by the number of tunnels and direction determined by the time at
which neurons are plated. Extracellular signals (spikes) were recorded using
the MEA. Network activity consisted of both tonic spikes and synchronized
bursts. Each spike train was smoothed with an exponentially decaying signal to
obtain a continuous waveform. Conditional Granger Causality (CGC) between
different electrodes was then computed using the GCCA toolbox [2] and results compared to conventional
cross correlogram analysis. CGC estimates of causal strength within tunnels and
between input and output wells were higher in the predicted feed-forward
direction (Fig 2) and paralleled results produced by conventional
cross-correlation metrics.